Evaluating probabilistic model checking tools for verification of robot control policies-Reference-Cited by-同舟云学术

Evaluating probabilistic model checking tools for verification of robot control policies

Published:2016-03-02 Issue:2 Volume:29 Page:287-299
ISSN:1875-8452
Container-title:AI Communications
language:
Short-container-title:AIC

Author:

Pathak Shashank¹²,Pulina Luca³,Tacchella Armando²

Affiliation:

1. iCub Facility, Istituto Italiano di Tecnologia, Genova, Italy. E-mail: Shashank.Pathak@iit.it

2. DIBRIS, Università degli Studi di Genova, Genova, Italy. E-mail: armando.tacchella@unige.it

3. POLCOMING, Università degli Studi di Sassari, Sassari, Italy. E-mail: lpulina@uniss.it

Publisher

IOS Press

Subject

Artificial Intelligence

Reference23 articles.

1. [1]E. Abrahám, N. Jansen, R. Wimmer, J. Katoen and B. Becker, DTMC model checking by SCC reduction, in: Seventh International Conference on the Quantitative Evaluation of Systems (QEST) 2010, IEEE, 2010, pp. 37–46.

2. [2]A. Aziz, V. Singhal, F. Balarin, R.K. Brayton and A.L. Sangiovanni-Vincentelli, It usually works: The temporal logic of stochastic systems, in: Computer Aided Verification, Springer, 1995, pp. 155–165.

3. Editorial: Special issue on machine learning in robotics;Bagnell;The International Journal of Robotics Research,2008

4. Preface to the special issue on probabilistic model checking;Baier;Formal Methods in System Design,2013

5. [5]M. Bozzano, A. Cimatti, M. Roveri and A. Tchaltsev, A comprehensive approach to on-board autonomy verification and validation, in: Proceedings of the 22nd International Joint Conference on Artificial Intelligence, IJCAI 2011, Barcelona, Catalonia, Spain, 16–22 July 2011, 2011, pp. 2398–2403.

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The 10,000 Facets of MDP Model Checking;Lecture Notes in Computer Science;2019

2. Formal Analysis of the PKMv3 Protocol;Mobile Networks and Applications;2017-09-21

3. Verification and repair of control policies for safe reinforcement learning;Applied Intelligence;2017-08-05

4. Neural Networks for the Output Tracking-Control Problem of Nonlinear Strict-Feedback System;IEEE Access;2017

5. More Adaptive Does not Imply Less Safe (with Formal Verification);Hardware and Software: Verification and Testing;2017